Detailed Description

Computes the corners in an image using a method based upon FAST9 algorithm suggested in [3] and with some updates from [4] with modifications described below.

It extracts corners by evaluating pixels on the Bresenham circle around a candidate point. If \( N \) contiguous pixels are brighter than the candidate point by at least a threshold value \( t \) or darker by at least \( t \) , then the candidate point is considered to be a corner. For each detected corner, its strength is computed. Optionally, a non-maxima suppression step is applied on all detected corners to remove multiple or spurious responses.

Segment Test Detector

The FAST corner detector uses the pixels on a Bresenham circle of radius 3 (16 pixels) to classify whether a candidate point \( p \) is actually a corner, given the following variables.

So when either of these two conditions is met, the candidate \( p \) is classified as a corner.

In this version of the FAST algorithm, the minimum number of contiguous pixels \( N \) is 9 (FAST9).

The value of the intensity difference threshold strength_thresh. of type VX_TYPE_FLOAT32 must be within:

\[ {UINT8_{MIN}} < t < {UINT8_{MAX}} \]

These limits are established due to the input data type VX_DF_IMAGE_U8.

Corner Strength Computation

Once a corner has been detected, its strength (response, saliency, or score) shall be computed if nonmax_suppression is set to true, otherwise the value of strength is undefined. The corner response \( C_p \) function is defined as the largest threshold \( t \) for which the pixel \( p \) remains a corner.

Non-maximum suppression

If the nonmax_suppression flag is true, a non-maxima suppression step is applied on the detected corners. The corner with coordinates \((x,y)\) is kept if and only if